Preface

Computing in context has become a necessity in modern intelligent IT applications. Context
is now more than just location. It is seen as a multi-dimensional space of environmental
aspects, even including non-physical facets such as emotions. Hence, models for represent-
ing context have evolved from using simple key-value pairs to using current methods and
techniques derived from artificial intelligence and knowledge management, e.g., logic, object
relationship models, and ontologies.
   Context and context-awareness are crucial not only for mobile and ubiquitous computing,
but span various application areas: collaborative software and web engineering, personal
digital assistants and peer-to-peer information sharing, health care workflow and patient
control, adaptive games and e-Learning solutions. In all these areas, context serves as a ma-
jor source for reasoning, decision-making, and adaptation, as it covers not only application
knowledge but also environmental knowledge.
   With the introduction of intelligent systems and automation, other needs arise for IT ap-
plications which are important for the systems’ users and may be solved or supported by
applying context. A crucial one is the understandability of an IT system, for explaining how
solutions are found, what the system is doing, and why it operates a certain way. Applied
methods and given advice have to be explained, so that the user can understand the process
and agree on decisions. Another vital feature is to provide uncertain or blurred information,
e.g., when using a tracking system in situations where either revealing the current position or
denying access to it would spoil the activity.
   Appropriate context management methods are an important prerequisite for using contex-
tual information. Advanced models, methods, and tools are needed to provide mechanisms
and techniques for structured storage of contextual information, to provide effective ways to
retrieve it, and to enable integration of context and application knowledge.
   With the use of mobile devices and current research on ubiquitous computing, the topic of
context-awareness is a major issue for future IT applications. Modeling and retrieving con-
text provides means to be integrated in modern knowledge management processes. Intelli-
gent solutions are needed to apply context, e.g., to cope with the fuzziness of contextual
information and, especially, because of mobility, with rapidly changing environments and
unsteady information sources. Advanced methodologies for determining or assigning a con-
text to a situation are required, which brings the need for Artificial Intelligence mechanisms
in context-aware applications.
   This second installment of the MRC workshop series on modeling and retrieval of context
reflected substantial interest and activity in this area, with nearly twice as many submissions
as MRC 2004. Special thanks go to the program committee and additional reviewers, for
their efforts and hard work in the reviewing and selection process. Further, we thank all the
authors who submitted articles to the workshop to make this program possible.


August 2005                Stefan Schulz, David B. Leake, Thomas R. Roth-Berghofer